ผลต่างระหว่างรุ่นของ "Probstat/notes/regression"

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== Model ==
 
== Model ==
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We consider two variables <math>X</math> and <math>Y</math> where <math>Y</math> is a function of <math>X</math>.  We refer to <math>X</math> as  independent or input variable, and <math>Y</math> as a dependent variable.  We consider linear relationship between independent variable and dependent variable.  We assume that there exist hidden variables <math>\alpha</math> and <math>\beta</math> such that
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<center>
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<math>Y = \alpha + \beta\cdot X + e,</math>
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</center>
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where <math>e</math> is a random error.  We further assume that the error is unbiased, i.e., <math>E[e]=0</math> and is independent of <math>X</math>.
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== The least squares estimators ==
 
== The least squares estimators ==
 
== Distribution of regression parameters ==
 
== Distribution of regression parameters ==
 
== Statistical tests on regression parameters ==
 
== Statistical tests on regression parameters ==

รุ่นแก้ไขเมื่อ 09:03, 7 ธันวาคม 2557

This is part of probstat.

In this section, we shall discuss linear regression. We shall focus on one-variable linear regression.

Model

We consider two variables and where is a function of . We refer to as independent or input variable, and as a dependent variable. We consider linear relationship between independent variable and dependent variable. We assume that there exist hidden variables and such that

where is a random error. We further assume that the error is unbiased, i.e., and is independent of .

The least squares estimators

Distribution of regression parameters

Statistical tests on regression parameters